Evidence mapPaperPMID 37504305Full record

ArticleCurrent issues in molecular biology2023

Insight into the lncRNA-mRNA Co-Expression Profile and ceRNA Network in Lipopolysaccharide-Induced Acute Lung Injury.

Yue Shen, Linjing Gong, Fan Xu, Sijiao Wang, Hanhan Liu, Yali Wang, Lijuan Hu, Lei Zhu

Open access · goldAbstract read
In one paragraph

Article in Current issues in molecular biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 1 country.

Yue ShenDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Linjing GongDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Fan XuDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Sijiao WangDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Hanhan LiuDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Yali WangDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Lijuan HuDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Lei ZhuDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Fudan University · CNSun Yat-sen University · CNThe First Affiliated Hospital, Sun Yat-sen University · CNWest China Hospital of Sichuan University · CNZhongshan Hospital · CN

Funding

National Natural Science Foundation of China 82070075
6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) participate in acute lung injury (ALI). However, their latent biological function and molecular mechanism have not been fully understood. In the present study, the global expression profiles of lncRNAs and mRNAs between the control and lipopolysaccharide (LPS)-stimulated groups of human normal lung epithelial cells (BEAS-2B) were determined using high-throughput sequencing. Overall, a total of 433 lncRNAs and 183 mRNAs were differentially expressed. A lncRNA-mRNA co-expression network was established, and then the top 10 lncRNAs were screened using topological methods.

Indexed as

acute lung injuryceRNA regulatory networkexpression profilehigh-throughput RNA sequencinginflammatory responselong noncoding RNAs

Identifiers

PMID37504305
PMCPMC10378513
OpenAlexW4385241719

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.